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How GitHub's culture and benefits helped me be the best version of myself. The post Transitioning as a hubber appeared first on The GitHub Blog .

The Argo CD project released a v3.5 release candidate in June 2026. This version adds mutual TLS enforcement for internal components. It also includes Git commit signature verification for supply chain security and native ApplicationSet management in the UI. The release also graduates two significant features: impersonation and Source Hydrator, from alpha to beta. By Claudio Masolo

Diagrid has announced the release of Dapr 1.18, introducing what it calls Verifiable Execution, a new set of capabilities designed to bring cryptographic trust, provenance, and tamper-evident execution records to distributed applications and AI agents. By Craig Risi

Welcome to Walmart deals for folks who’d rather not shop at Amazon. These are the best gadget deals at Walmart this Prime Day.

From October this year Samsung will roll out a variety of new paid tiers for access to its SmartThings API, including a $4.99 monthly plan for "non-commercial, individual developers." It won't just be developers that pay the price though. Some more advanced smart home users are likely to fall afoul of the rule change if […]

After testing each of the MacBooks myself, here's my honest advice on which is right for you.

It's Day Four. Somehow it's still Prime Day. The deals are live. The deals are wild. The deals are almost feral. We are still here in the trenches digging up the deals and trends.

Kids love 3D printers almost as much as K-Pop Demon Hunters. Just give in and get one.

From AirPods to on-ears, we’ve tested hundreds of pairs of headphones. Here are the best deals from Amazon’s biggest sale event.

Qatar has become the place where FIFA experiments with the next generation of football technology. The results are already visible across this year’s World Cup.

Why adaptability beats perfection in startup software development The Startup Trap: Building for a Future That Doesn't Exist Yet Many startup founders make the same mistake. They spend months building the "perfect" product architecture. The code is clean. The design patterns are flawless. The test coverage is near 100%. The infrastructure can scale to millions of users. There's just one problem: They don't have any users. In the startup world, survival depends on learning faster than competitors, not on creating the most elegant codebase. Product-market fit is uncertain. Customer needs change weekly. Business models evolve. Features that seemed critical last month become irrelevant the next. In that environment, the biggest advantage isn't perfect code. It's malleable code . Code that can bend, adapt, and evolve as the business learns. What Is Malleable Code? Malleable code is software that is easy to change. It isn't necessarily perfect. It isn't over-engineered. It isn't designed to solve every future problem. Instead, it's designed to support continuous experimentation. Malleable code allows teams to: Launch MVPs quickly Test assumptions rapidly Respond to customer feedback Pivot when necessary Add new features without major rewrites Remove failed features with minimal effort Think of it this way: Perfect code optimizes for certainty. Malleable code optimizes for uncertainty. And startups operate almost entirely in uncertainty. When you're still searching for product-market fit, the ability to adapt is often more valuable than technical elegance. Why "Perfect" Code Often Hurts Startups Software engineers love solving technical problems. It's natural. Building a scalable architecture feels productive. Refactoring code feels productive. Designing the perfect system feels productive. But startup success isn't measured by code quality. It's measured by business outcomes. Questions such as: Are customers using the product? Are they paying for it? Are they returning? A

I've been digging into malware analysis lately, and one thing became clear pretty fast: before you ever touch a debugger or run a suspicious binary, you need to understand the landscape — what malware actually is, how it's classified, and what a safe, repeatable analysis workflow looks like. This post is my attempt to organize that foundation. No flashy exploit walkthrough here — just the core concepts I think anyone starting out in malware analysis needs to internalize first, because skipping this step is how people either get sloppy or get burned (sometimes literally infecting their own host machine). Problem Statement If you search "malware analysis tutorial," you mostly get tool-specific guides — "how to use Ghidra," "how to use Process Monitor" — without context on why you'd choose static vs. dynamic analysis, or how to build a lab that won't accidentally compromise your real network. I wanted to write down the methodology layer first: the classification of malware, the four analysis approaches, and the non-negotiables of lab isolation. This is the stuff that makes the tool-specific tutorials actually make sense later. What Malware Analysis Actually Is Malware analysis is the study of a malicious program's behavior — the goal is to understand what it does, how it got in, and how to detect/eliminate it across an environment, not just on one infected machine. A few concrete objectives that stuck with me: Determine the nature of the malware — is it an infostealer, a keylogger, a spam bot, ransomware? Understand the compromise — how did it get in, and what's the blast radius? Infer attacker motive — banking credential theft usually points to financial motive; persistence + C2 beaconing might point to espionage. Extract network indicators — domains, IPs, User-Agent strings — for network-level detection. Extract host-based indicators — registry keys, dropped filenames, mutexes — for endpoint-level detection. This connects directly to something called the Pyramid of P

Mitigating Hallucinations in Theology AI: Implementing Groundedness Evaluation Pipelines For software developers and indie hackers, the era of building generic wrapper APIs is over. The real value now lies in highly specialized, niche vertical applications. One of the most fascinating, complex, and underserved niches is the intersection of artificial intelligence and religious doctrine. Building a catholic ai tool presents unique software engineering challenges. Unlike general-purpose chatbots, a theology ai application cannot afford to "hallucinate" or generate creative interpretations of established doctrines. In this space, an inaccurate answer is not just a software bug; it is a theological error. To build a high-quality, trustworthy catholic ai app , developers must move past basic prompt engineering. We must implement robust groundedness evaluation pipelines. This article explores the technical journey of building a specialized catholic ai chatbot , the catholic church stance on ai , our choice of tech stack, and how to build a production-grade groundedness pipeline to keep your AI aligned with official church teachings. The Catholic Church Stance on AI: Designing for Ethics and Trust Before writing a single line of Dart, Swift, or Python, we must understand the ethical landscape of ai and theology . The Vatican has taken an surprisingly proactive approach to artificial intelligence. Pope Francis has frequently spoken on the topic, advocating for "algor-ethics"—the ethical development of algorithms. The catholic church stance on ai emphasizes that technology must serve human dignity and remain aligned with truth. ┌─────────────────────────────────┐ │ The Vatican's Algor-ethics │ └────────────────┬────────────────┘ │ ┌─────────────────────────┴─────────────────────────┐ ▼ ▼ ┌──────────────────┐ ┌──────────────────┐ │ Human Agency │ │ Doctrinal Truth │ │ AI must assist, │ │ AI must not alter│ │ never replace │ │ established dogma│ └──────────────────┘ └─────────

Want to turn a small ESP32 board into a mini arcade game you can actually play? This ESP32 OLED Mini Shooter Game uses a 128x64 OLED display and two push buttons to create a simple shooter experience. The player moves left and right, bullets fire upward, and enemies fall from the top of the screen. It is a small project, but it already feels like a real handheld game once the display starts updating. This build is a great next step after basic OLED and button tutorials. Instead of only printing text or drawing one shape, the code manages several moving objects at the same time. It tracks the player, bullets, enemies, collisions, and game-over state. The screen is divided into a simple grid. The 128x64 OLED becomes a 16x8 playfield, where each tile is 8x8 pixels. This makes object movement easier to understand because the player, enemies, and bullets move by grid position instead of raw pixel math. Why build it? This project teaches interactive programming on real hardware. The ESP32 reads button input, updates game objects, checks collisions, and draws the next frame on the OLED. That is much more active than a normal sensor display project. It also teaches timing without blocking the whole game flow. The code uses millis() to control when bullets and enemies update, so they can move at different speeds. This is useful because many embedded projects need timed actions without stopping everything else. What you'll learn ESP32 OLED display control - drawing text, squares, circles, and game objects on an SSD1306 screen. Custom I2C pins - using Wire.begin(5, 19) so the OLED uses GPIO5 for SDA and GPIO19 for SCL. Button input handling - reading two push buttons for left and right movement. Debounce logic - preventing one press from being counted many times. Grid-based game design - turning a 128x64 screen into a simple 16x8 game map. Game object arrays - storing multiple bullets and enemies with active/inactive states. Timer-based updates - using millis() to move bullets

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Cross-posted from noflattery.com/decide — where I ran this exact question through a council of four different frontier models and let them argue it out. You're a solo founder at ~$8K MRR. You have runway for exactly one full-time hire. Which role unlocks the most growth? (A) a second engineer to ship features faster (B) a marketer to build a real acquisition channel (C) a customer-success / support hire to cut churn and free your time (D) a salesperson to chase larger deals The intuitive answer for most technical founders is A — more shipping velocity. The case below is for C , and it's stronger than it looks. (With one caveat that can flip the whole thing — stick around for it.) TL;DR: At ~$8K MRR solo, hire customer success first if churn is real or support is eating your week . If voluntary churn is under ~3% and support is light, hire a marketer instead. Engineer and sales come later. The case for customer success first 1. Churn quietly eats growth before features can add it. At $8K MRR, 5% monthly churn is ~$400/month bleeding out before you grow an inch. Across bootstrapped SaaS in the $5–15K MRR band, the strongest predictor of reaching $50K isn't feature velocity or channel — it's net revenue retention above 90% . That's a customer-success function, not an engineering one. 2. You are the bottleneck, and support is eating you. As a solo founder you're doing product, sales, billing, and support. If support takes ~15 hours a week, that's nearly 40% of your capacity — and it's the cheapest thing to hand off. A CS hire costs less than a senior engineer or an experienced salesperson, and it buys back the hours (and the headspace) you need to think strategically again. 3. It's a research department in disguise. A CS hire generates the highest volume of qualitative signal: why people leave, what they actually use, what they'd pay more for. An engineer builds what you think users want. CS tells you what they actually need — which means the engineer you hire next buil

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It’s been hot in London this week. Really hot. A dangerous heat wave has hit Western Europe. Yesterday, the UK recorded its highest ever June temperature at 36.1 °C (about 97 °F). But as the weather app on my phone confirmed, it felt like 39 °C. It’s frightening that we are seeing such temperatures in…

We've gone from A to Z to find Amazon's best Prime Day deals on the gear worth owning.